Call for Papers
⭐ Submissions are live at our Open Review page ⭐
Full paper submission and co-author registration deadline: April 01, 2023 AoE (Note: previously, there were separate deadlines for the abstract and paper submission. These are now combined, and the deadline has been extended. You needn’t submit anything before April 1st.)
Author notification: May 10, 2023 AoE
Camera-ready paper submission: Saturday July 1, 2023 AoE
The site will start accepting submissions on: Friday January 9th, 2023
The 14th annual conference on Sampling Theory and Applications is an interdisciplinary forum for mathematicians, engineers, and applied scientists to share recent advances in sampling theory and discuss trends in the field and its applications. We now invite submissions of original research in topics including:
Sampling Theory
- sampling of space-time deterministic or stochastic signals
- sampling on the sphere and on more general manifolds
- sampling on graphs
- compressive sensing
- sampling theory in reproducing kernel Hilbert and Banach spaces
- frame theory and its applications in sampling theory
- shift-invariant and spline-type spaces
- approximation error analysis and local reconstructions
- analytic number theory and lattice point methods in sampling expansions
- sampling in coorbit theory and group representations
- aspects of function spaces in sampling theory (Sobolev spaces, Besov spaces, Wiener amalgam spaces and others)
- operator and functional analytic methods related to the above topics
Signal and Image Processing
- audio and image processing
- signal processing and inverse problems on graphs
- signal transforms such as the scattering transform
- wavelets, shearlets, Gabor expansions
- atomic decompositions and related transforms
- information theory and communications
- analog to digital conversion and quantization
- phase retrieval problems
- control theory methods in signal processing
- interaction between inverse problems, signal analysis, and image processing
- operator and functional analytic methods related to the above topics
Data Analysis
- machine learning and neural networks
- high dimensional data analysis and manifold learning
- application of frame theory in data analysis
- mathematical foundations of deep learning
- probabilistic methods for data analysis
- reproducing kernel methods in machine learning and data analysis
- inverse problems, data assimilation and uncertainty quantification
- sparsity in data analysis
- quantum computing and quantum learning
- operator and functional analytic methods related to the above topics
Contributions from authors attending the SampTA conferences will be published in IEEE Xplore.
Our submission instructions and review process follow standard NeurIPS Guidelines.
Formatting Instructions:
Submit a PDF of no more than 4 pages, including figures and tables, using the IEEE style in LaTeX:
\documentclass[conference] {IEEEtran}
References do not count towards the page limit. Include as many you’d like.
Submissions that try to squeeze in extra text by tweaking the stylesheet may be summarily rejected.
Accepted submissions will be granted one extra page of content for the camera-ready version.
Double-blind reviewing:
Submissions must be anonymized and carefully stripped of identifying information. This applies not only to the main body of the paper, but also the supplement and any linked resources (e.g. GitHub repositories).
OpenReview
Submissions can be created and managed through our Open Review page.
Supplementary Material
You may include up to 100MB of supplementary material (appendices, proofs, data, source code), in either PDF or ZIP format. Take care that this is anonymized! Reviewers have no obligation to review the supplementary material.
Preprints
You are allowed to distribute non-anonymous preprints of work submitted to SamPTA, and may also submit work to SampTA that has been previously distributed on non-anonymous non-peer reviewed websites (like arXiv).
Author Responses
After initial reviews are distributed, authors will have one week to respond. Authors must maintain anonymity in their responses.
After the response period, accepted papers will be made public, along with their anonymous reviews and comments. Authors of rejected papers may elect to have their deanonymized rejected paper made public in OpenReview.
Publication of Accepted Submissions
We encourage all authors to make their code and data available along with the publication. Additionally, all camera-ready papers must include a funding disclosure.